Optimization of the treatment of hydrocephalus by the non-invasive measurement of the intra-cranial pressure

This thesis work aims to optimize the treatment of hydrocephalus. It consists of two distinct objectives: the optimization of the diagnosis of patients implanted with a shunt system for the derivation of cerebro-spinal fluid (CSF) and the optimization of the treatment by a better understanding of the fluidic characteristics of shunts. The diagnosis optimization was addressed by a pressure sensor allowing for the measurement of the intra-cranial pressure (ICP). It has been characterized experimentally in vitro and in vivo in animals. The pressure sensor is integrated along a shunt system for the derivation of CSF and it can be interrogated by telemetry. The non-invasive access to the ICP will allow the physician to verify that the implantation of a shunt system has successfully restored a physiological ICP level. It will also provide a method to verify that the shunt is not blocked and fully functional. Simple mathematical models of the hydrodynamics of shunt systems used clinically are presented to address the second objective. These simple models are verified experimentally by characterizing the shunts on a setup developed for that purpose. This setup allows the characterization of non-bijective flow-pressure characteristics. The integration of mathematical models of shunt systems in a broader model describing the circulation of CSF in a patient implanted with a shunt will permit to predict the dynamics of the CSF circulation. It will also be a useful tool for shunt manufacturers to identify shunt characteristics critical to successfully restore a physiological condition after implantation. The results of this thesis work are presented in the form of an introduction, three scientific publications and a short conclusion. The motivations for the thesis work are presented in the introduction chapter along with background information about hydrocephalus and its treatment. A mathematical model describing the circulation of CSF is described in the same chapter. This model illustrates the interactions between the fluidic constituents of the cranial vault that lead to a physiological CSF circulation and ICP level. This model has been adapted to account for the implantation of a shunt system. The key technical characteristics of the pressure sensor are exposed in the subsequent section along with the experimental techniques and a short summary of the publications and patents. The pressure sensor is described in the first publication with a focus on the pressure transducer, the original sensor encapsulation technique, the electronics embedded in the sensor and the telemetry technique. A capacitive pressure transducer, which provides an accurate measurement of the absolute pressure, has been developed. The transducer technology guarantees a minimal drift of its characteristics with time. The design and the key manufacturing steps of the transducer are exposed. A hermetically closed capsule protects the sensor electronics. The effect of the packaging components and the assembly techniques on the sensor characteristics are analyzed. An analysis of the water diffusion through the walls of the capsule is presented since resistance to water permeation is a critical characteristics of the packaging. Minimal drift with time can only be achieved if the atmosphere in the capsule is extremely stable. The packaging provides a barrier to water diffusion in order to keep a constant low humidity level in the sensor. The telemetric link between the sensor and the external reading unit is provided by an inductive coupling between two loop antennas. The coupling allows the simultaneous transmission of power to the sensor and of the pressure data to the external unit. The fundamental characteristics of the telemetric link are described. The interfacing electronic components are integrated in an ASIC that consumes a minimal amount of energy. Lastly, the experimental characterization of the accuracy of the sensor and its thermal stability are presented. The second publication is focused on the in vivo characterization of the pressure sensor in animals. An animal model of hydrocephalus has been developed in order to characterize the correlation between the pressure measured by the sensor integrated into a shunt system and a reference provided by a direct measurement of the ICP in the ventricles of the brain. Hydrocephalus was induced in dogs by injection of kaolin and glue in the cisterna magna. The time course of hydrocephalus induction was followed by the measurement of the size of the ventricles by an ultrasonic imaging technique. Approximately 50 days after the injection of kaolin and glue, a shunt system integrating a pressure sensor was implanted between the brain ventricles and the peritoneum. A reference pressure sensor was also implanted in the ventricles. The pressure was then measured for up to 48 hours. The correlation between the pressure in the shunt and the intra-ventricular pressure is documented in the publication. The advantages associated with the measurement of the pressure in the shunt versus an intra-ventricular measurement technique are discussed and the pressure sensor is compared with other published sensors. The third publication describes three commonly used shunt systems by simple hydrodynamic mathematical models. A setup allowing the characterization of shunt systems having a non-bijective pressure-flow characteristics is presented. The experimental characteristics of the three shunt systems is compared to the theoretical models. The "pressure-controlled" and "flow-controlled" terminologies, which are frequently used in the clinical field, are discussed in the context of the hydrodynamic characteristics of shunts. Four patent applications have been submitted in the course of this thesis work. The three first applications have been granted, and the last one is filed. The first patent protects the pressure sensor encapsulation technique. The second patent protects the concept of a shunt system allowing the non-invasive adjustment of the resistance of the shunt valve. This concept has been developed as a result of the analysis of the critical parameters to successfully restore a physiological ICP level by the mathematical model of the CSF circulation. The third patent protects the use of the pressure sensor packaging technique for a flow sensor integrated in the shunt system. The last application protects the mechanism that regulates the power of the radio-frequency wave emitted by the external reading unit on the basis of the voltage induced in the sensor. The last chapter, entitled "Conclusion and Perspectives" summarizes the outcome of this thesis work in reference to the optimization of the treatment of hydrocephalus. This work laid the foundation for the use of the sensor in humans through a clinical study. The ICP data gathered during such a study would then allow the validation of the mathematical model of CSF circulation presented in this thesis.

Access to vaccine technologies in developing countries: Brazil and India

Patrick Gaulé

This study, conducted by visits, interviews, and literature search, analyzes how vaccine manufacturers in Brazil and India access technologies for innovative vaccines: through collaborations with academia and research institutions, technology transfer agreements with multinational corporations, public sector, or developing country organizations, or by importation and finishing of bulk products. Each has advantages and disadvantages in terms of speed, market, and ability to independently produce the product. Most manufacturers visited are very concerned about avoiding patent infringement, which might result in undeveloped or delayed products because of a lack of mastery of the patent landscape. Disregarding the patent picture could also threaten the market of a potential product. Although it is too soon to assess the effects of TRIPS on vaccine technology access in Brazil and India, a good understanding of intellectual property management will be useful. A case study on development of a new combination vaccine illustrates these findings.

2007

Fluid Structure Interaction Simulations of Physiological Blood Flow in the Aorta

Paolo Crosetto, Simone Deparis, Dimitrios Kontaxakis, Alfio Quarteroni, Philippe Reymond, Nikolaos Stergiopulos

The numerical tools to simulate blood flow in the cardiovascular system are constantly developing due to the great clinical interest and to scientific advances in mathematical models and computational power. The present work aims to address and validate new algorithms to efficiently predict the hemodynamics in large arteries. The latter rely on finite elements simulation of the fluid-structure interaction between blood flow and arterial wall deformation of a healthy aorta. Different sets of boundary conditions are devised and tested. The mean velocity and pressure time evolution is plotted on different sections of the aorta and the wall shear stress distribution is computed. The results are compared with those obtained with a rigid wall simulation. Pulse wave velocity is computed and compared with the values available from the literature. The flow boundary conditions used for the outlets are obtained using the solution of as one dimensional model. The results of the simulations are in agreement with the physiological data in terms of wall shear stress, wall displacement, pressure waveforms and velocities.

Elsevier2011

Modeling and Simulation of Energy Efficient Milling Process Plans for Prismatic Parts

Nenad Nesic

The milling process has been continuously optimized from many aspects: forces, velocities, stability, quality. Numerous papers have been published that report results in the domain of toolpath optimization with criteria such as raising the quality of the machined part, obtaining a stable machining process and maximizing the material removal rate. However, only recently researchers have started investigating the ecological impact of machining processes. With the constantly increasing prices of electrical energy and all environmental problems caused by the production and waste of the energy, it has become indispensable to look for ways to optimize machining processes from the energy consumption aspect, too. It is in this domain, then, that the work described in this dissertation contributes – to add a new criterion for the sustainable operation of machine tools: reducing the energy consumption during the use phase of the machine tool. The total energy spent in a machining process is the sum of power spent by all machine tool subsystems multiplied by the time that they are working. Therefore, the operating strategies for increasing energy efficiency for the high-speed machining processes must be oriented towards the reduction of the total machining time (productive and unproductive) and reduction of instantaneous consumed power in the machining process or, preferably, both. There are many causes for milling process time and energy inefficiency. The major sources of potential time reductions include: (i) the issues related to the geometry and topology of the toolpath („air-time”, overlapping segments, gouge and uncut regions, orientation of the toolpath), (ii) the issues related to the kinematics of the feed drives (the feed velocity/acceleration profile). The possible domains for power consumption reduction are related to the forces that exist in the machining process (cutting, inertial, gravitational and friction forces). The power invested to overcome the cutting force is necessary for the machining process but its consumption should be optimized through constant cutting engagement and feedrate scheduling strategies. The other forces are responsible for the pure mechanical power loss and they should be minimized. The optimization variables for inertial and gravitational forces include the feed motion profile and moving mass configuration, while friction losses are load and/or velocity dependent. In addition, there are some power losses in the electric components of machine tool drives (electrical power losses), whose dependency on velocity and mechanical load can also be modeled. Despite many research efforts to analyze and model the phenomena causing inefficiency of the machining process, they are usually not taken into account during milling process planning. In fact, rare are the attempts to use this knowledge to optimize the milling process with more than one of the above mentioned criteria. The reason for that lies in the fact that increasing the instantaneous values of tool engagement and feedrate in order to minimize total machining time also increases the consumed power and, indirectly, deteriorates the tool and/or destabilizes the cutting process. The existence of conflicting criteria in the objective functions imposes the use of evolutionary algorithms for multiobjective optimization. The process of experimental validation of such an optimization model requires costly and complex external hardware setup and it is also time consuming. Hence, there is an emerging need for the development of an accurate model, which would be used for the simulation of the milling process and testing the competing optimization strategies. The ultimate goal of contemporary manufacturing science and engineering is the development of a holistic virtual machine tool system. The motivation of this PhD research is to contribute to this objective by developing the “virtual milling process for prismatic parts (produced by 2.5D milling)”. This category of objects is selected, because the majority of CNC milling tasks can be performed using 2.5D milling. A very large number of mechanical parts are prismatic (their geometry consists exclusively of features that represent 2D contours extruded in a perpendicular direction). Parts that are even more complex are usually produced from a blank by a 2.5D roughing and 3D–5D finishing. Therefore, development of an accurate model of a 2.5D milling process represents a significant contribution to manufacturing engineering. Starting with above given problem description, we have defined the following research objectives: 1. Model power and energy consumption of a 2.5D milling machine as a function of the toolpath geometry (curvature and continuity), cutting engagement, real feedrate profiles and spindle rotational speed, taking into account moving mass configuration, all power losses (mechanical and electrical) in feed-axis and spindle drives and electromechanical constraints of servo drives; 2. Design an integrated software environment for simulation of the developed models; 3. Validate the model experimentally; 4. Demonstrate the potential of its use for multi-objective process optimization. Cutting engagement calculation is performed by using two competing methodologies, in order to make a comparison of their performances. The first one, the pixel based method, is based on discrete image processing, while the other, the exact method, is based on Boolean operations and vector geometry. The tests performed in more than 20 feature/toolpath combinations demonstrate that the exact method is more precise whereas the pixel-based method is computationally much faster. The machine tool operator commands a constant feedrate value. During the process, based on his/her subjective judgment, he/she can manually tune it to keep the process in the desired boundaries. One of the objectives of this research is to predict the real feedrate values so that they can be integrated in the part program before the process start. The feasible profiles of feed velocities for each toolpath segment are analyzed by answering the following questions: can the commanded feedrate be achieved and with what sequence of acceleration and deceleration phases, how much the tool has to slow down in corners and how does the feedrate profile degenerate in segments where the commanded feedrate cannot be reached? In order to determine all forces and torques, a machine tool model is developed. The following subsystems are modeled as rigid bodies (without vibrations): feed motor shaft, transmission, lead screw/nut pair, lead screw bearings, guides (sliding and rolling design), table with the workpiece and electrospindle (rotor, stator and bearings). All kinetic variables (linear and angular speeds; cutting, inertial and friction forces and torques) are then calculated in the joints of this multi-body system. The modeling of all speeds, forces and torques that occur in the machine tool system during the machining process, allows for calculation of various indicators of process time and energy efficiency: material removal rate, total machining time, useful power (invested in cutting), power loss due to the friction in the joints, power losses in electrical motors, electrical energy consumption of feed and spindle drives. In order to assess the accuracy and the reliability of the developed model two sets of experiments have been performed. The model validation is performed on several subsystem levels and the simulation results show a very good compliance with the experimental results. The first experimental setup consists of the force dynamometer, to measure cutting force components in linear axis directions, two laser optical position sensors, to measure the real feedrate and the power sensor, to measure the total power consumption of the machine tool electrical motors. The machining process was performed on the 6-axis machining center C.B. Ferrari A152 and the data acquisition platform was developed in LabVIEW 2010. The second experimental setup consists of the torque dynamometer, to measure the cutting torque directly on the spindle, the built-in current sensor that measures the motor current proportional to the electrical power consumed by the spindle and, again, the power sensor, to measure the total power consumption of the machine tool electrical motors. This time, MIKRON HPM 600U, a 5-axis milling machine equipped with the controller iTNC530, was used for the experimentation. The developed model is ready for practical implementation. Several examples have been prepared to demonstrate its capabilities in the domains of milling process simulation, sensitivity analysis and prospective optimization strategies. These examples include the prediction of various kinetostatic variables for given toolpaths, choice of the optimum machining strategy (minimization of machining time, moving mass and energy consumption) and process optimization by feedrate scheduling (reduction of cutting force fluctuation). As a conclusion, the major contribution of this PhD research is the development of a comprehensive rigid-body dynamics model of a machine tool system, aimed for the generation, simulation and optimization of 21⁄2D milling process plans. The model features several novelties compared to existing approaches: (i) it takes into account the machine tool rigid body dynamics and real tool kinematics in toolpath planning, (ii) it predicts all mechanical and electrical power losses in the machine tool system (iii) it allows the modeling of machine tool system electromechanical constraints. The model was experimentally validated on two real machine tools in different workshops and its capabilities for the simulation of different toolpath patterns and optimization of process parameters were successfully demonstrated using several examples.

EPFL2012

Modeling and Simulation of Energy Efficient Milling Process Plans for Prismatic Parts

Nenad Nesic

EPFL2012